From a one-line idea to a buildable SDLC.
AI-SDLC turns a plain-language idea into an engineer-grade plan — requirements, architecture, security, and testing — then audits the code you already have and helps you build it. Planning, guidance, and delivery in one place, so what you design actually ships.
AI-SDLC is an AI development companion for the entire software lifecycle — not just code completion. Describe what you want to build and it interviews you, generates a full engineer-grade documentation pack (requirements, architecture, security, testing, and a project-specific prompt playbook), audits the code you already have, and guides the build to completion. It's made for everyone from non-technical founders to AI-first teams who want to go from idea to shipped software in one place.
Key capabilities.
What AI-SDLC delivers — outcomes, not slideware.
AI Project Wizard — idea to full SDLC
An adaptive interview turns a one-line idea into a complete engineer-grade plan — requirements, architecture, security, testing, and a ready-to-work backlog — with suggested answers whenever you're unsure.
Approve, then generate live
Watch your entire documentation pack build in real time and sign off on your requirements before the full run, so the whole plan stays grounded in a spec you approved.
Project X-Ray — deep codebase audit
Audit any existing codebase for quality, exposed secrets, and dependency risk, and compare two projects side by side with an AI analyst you can question directly.
Model Lab — pick the right model
Compare leading AI models on capability and cost before you commit, so every task runs on a model you've actually evaluated.
Implementation Hub & BuildBot
Turn the plan into shippable steps with a guided build playbook and an AI agent scoped to each document, so what you designed actually gets built.
A prompt playbook for every project
Every build ships with 100+ tailored prompts and a recommended tool set, so you and your team know exactly what to run at each stage.
From start to shipped.
- 01
Describe your project
Start with a plain-language idea — no formal spec required.
- 02
Answer the AI's questions
An adaptive interview pins down scope, constraints, and goals, with suggested answers whenever you're stuck.
- 03
Review, then generate
Approve your requirements, then watch your full engineer-grade pack and prompt playbook build live.
- 04
Build with guidance
Follow a guided playbook with a per-document AI agent that turns the plan into working software.
- Turn a plain-language idea into a complete, engineer-grade SDLC
- Scope any project through an adaptive AI interview
- Generate requirements, architecture, security, and test plans in one pass
- Audit any codebase for quality, exposed secrets, and dependency risk
- Compare leading AI models on capability and cost
- Build with a guided playbook and a per-document AI agent
- Edit, regenerate, and export your full documentation pack
Good questions.
What does AI-SDLC actually generate?
For every project it produces a complete engineer-grade pack — product requirements, app flow, recommended tech stack, backend and frontend guidelines, security guidelines, test cases, an implementation plan, a setup guide, and architecture diagrams — plus 100+ tailored prompts and a ready-to-work backlog. Everything builds live, is editable inline, and exports in a single download.
Does it work with my existing codebase?
Yes. Project X-Ray audits any existing codebase and reports its technology stack, code quality, exposed secrets, and dependency risk — and you can compare two projects side by side and ask an AI analyst about the results.
How is this different from an AI coding assistant?
Autocomplete tools help you type code faster; AI-SDLC covers everything around the code — scoping the project, producing the planning, architecture, security, and testing documentation, auditing real codebases, and guiding implementation — so it complements a coding assistant rather than replacing it.
Is my code handled securely?
Yes. Sign-in is verified, your private keys stay protected on the server, and you can export or permanently delete your account and data whenever you want.
How is it priced?
Start free, then choose a paid plan from $29 to $99 a month for individuals, professionals, and teams — each unlocking more projects, more codebase audits, and priority processing. Annual billing works out to roughly ten months' price for twelve.